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How to Extract Solid or Dashed Arrow Styles from a Visio Diagram

Steve K Oct 1, 2026 869 views

Question details

The user needs to identify and extract the line styles (solid or dashed) of arrows and connectors in a Visio diagram to export flow classification data to Excel via a Python script.

How to Extract Solid or Dashed Arrow Styles From a Visio Diagram

Product: Microsoft Visio
Device & OS: not provided
Scenario: Automating the extraction of diagram flow information to categorize connections in an exported Excel spreadsheet.
Observed behavior: To correctly classify the exported flow information, the script must inspect the ShapeSheet properties of each connector to distinguish between solid and dashed line formats.

Before you start

Ensure you have your Python environment set up with the necessary COM automation libraries (such as pywin32) and verify that the target Visio file is accessible.

Solution 1Recommended

Read the ShapeSheet LinePattern Cell via Python Automation

Extract the line style by directly querying the ShapeSheet LinePattern properties of each connector shape.

Microsoft Visio controls the visual appearance of connector lines through its ShapeSheet data. By accessing the LinePattern cell for each shape via the Visio Object Model, you can determine exactly how the line is rendered.

Connect to the Visio Application

Use a library like `win32com.client` in Python to initialize the Visio application instance and open your target `.vsdx` diagram.

Loop Through Diagram Shapes

Iterate through the `Shapes` collection on the active Visio page to find and isolate the connectors or directional arrows.

Read the LinePattern Cell

Access the LinePattern cell in the ShapeSheet for each connector. In the Visio object model, this can typically be retrieved by querying `Shape.Cells("LinePattern").ResultIU`.

Map the Pattern Values

Evaluate the returned numerical values to classify the flow. Generally, a value of 1 indicates a solid line, and a value of 2 indicates a dashed line. Since Visio supports numerous custom line patterns, always inspect a sample of the actual values used in your specific diagram to ensure accurate mapping.

Read the ShapeSheet LinePattern Cell via Python Automation

Custom Line Patterns: If your diagram uses custom themes or specific templates, dashed lines might utilize values other than 2. Always run a quick test script to print out the LinePattern values of known solid and dashed shapes in your file.

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Process Your Exported Visio Flow Data with WPS Office

After successfully extracting your Visio diagram flow data via Python, you can seamlessly open, manage, and share the exported results in Excel format using WPS Office. It provides a lightweight, powerful, and free alternative to the Microsoft Office suite.

1. Open the Exported Data: Launch WPS Spreadsheets and open the .xlsx file generated by your Python Visio automation script.
2. Format the Flow Data: Use built-in conditional formatting or data filters to easily highlight or separate the "Solid" and "Dashed" flow categories.
3. Save and Share: Save your categorized flow classifications securely in standard .xlsx format to share with your engineering or analytics team.

Fully compatible with Microsoft Excel (.xlsx) formats exported by your Python scriptsLightweight and fast, ideal for managing large automation data dumpsFamiliar spreadsheet interface requires zero learning curveComprehensive, free alternative to the Microsoft Office suite

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Frequently Asked Questions

What does a LinePattern value of 0 mean in Visio?

A LinePattern value of 0 in a Visio ShapeSheet typically means the line is invisible or has no line pattern applied, meaning the stroke will not render.

Can I read Visio ShapeSheet properties using Python without having Visio installed?

If you are using COM automation (like pywin32), Microsoft Visio must be installed on the machine running the script. If Visio is not installed, you would need to parse the raw XML data inside the unzipped .vsdx file archive manually.

How do I write the extracted Visio line styles to an Excel file?

Within your Python script, you can use popular libraries like `pandas` or `openpyxl` to compile the extracted shape properties into a dataframe or dictionary, and then directly write that structured data out to a new .xlsx file.

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